def _get_grouped_dicoms(dicom_input):
"""
Search all dicoms in the dicom directory, sort and validate them
fast_read = True will only read the headers not the data
"""
# if all dicoms have an instance number try sorting by instance number else by position
if [d for d in dicom_input if 'InstanceNumber' in d]:
dicoms = sorted(dicom_input, key=lambda x: x.InstanceNumber)
else:
dicoms = common.sort_dicoms(dicom_input)
# now group per stack
grouped_dicoms = [[]] # list with first element a list
timepoint_index = 0
previous_stack_position = -1
# loop over all sorted dicoms
stack_position_tag = Tag(0x2001, 0x100a) # put this there as this is a slow step and used a lot
for index in range(0, len(dicoms)):
dicom_ = dicoms[index]
stack_position = 0
if stack_position_tag in dicom_:
stack_position = common.get_is_value(dicom_[stack_position_tag])
if previous_stack_position == stack_position:
# if the stack number is the same we move to the next timepoint
timepoint_index += 1
if len(grouped_dicoms) <= timepoint_index:
grouped_dicoms.append([])
else:
# if it changes move back to the first timepoint
timepoint_index = 0
grouped_dicoms[timepoint_index].append(dicom_)
previous_stack_position = stack_position
return grouped_dicoms
def _get_grouped_dicoms(dicom_input):
"""
Search all dicoms in the dicom directory, sort and validate them
fast_read = True will only read the headers not the data
"""
# Order all dicom files by InstanceNumber
dicoms = sorted(dicom_input, key=lambda x: x.InstanceNumber)
# now group per stack
grouped_dicoms = [[]] # list with first element a list
timepoint_index = 0
previous_stack_position = -1
# loop over all sorted dicoms
stack_position_tag = Tag(
0x2001, 0x100a) # put this there as this is a slow step and used a lot
for index in range(0, len(dicoms)):
dicom_ = dicoms[index]
stack_position = 0
if stack_position_tag in dicom_:
stack_position = common.get_is_value(dicom_[stack_position_tag])
if previous_stack_position == stack_position:
# if the stack number is the same we move to the next timepoint
timepoint_index += 1
if len(grouped_dicoms) <= timepoint_index:
grouped_dicoms.append([])
else:
# if it changes move back to the first timepoint
timepoint_index = 0
grouped_dicoms[timepoint_index].append(dicom_)
previous_stack_position = stack_position
return grouped_dicoms
def _create_bvals(sorted_dicoms, bval_file):
"""
Write the bvals from the sorted dicom files to a bval file
"""
bvals = []
for index in range(0, len(sorted_dicoms)):
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[index][0]
else:
dicom_headers = sorted_dicoms[index]
bvals.append(common.get_is_value(dicom_headers[Tag(0x0019, 0x100c)]))
# save the found bvecs to the file
common.write_bval_file(bvals, bval_file)
def _create_bvecs(sorted_dicoms, bvec_file):
"""
Calculate the bvecs and write the to a bvec file
# inspired by dicom2nii from mricron
# see http://users.fmrib.ox.ac.uk/~robson/internal/Dicom2Nifti111.m
"""
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[0][0]
else:
dicom_headers = sorted_dicoms[0]
# get the patient orientation
image_orientation = dicom_headers.ImageOrientationPatient
read_vector = numpy.array([float(image_orientation[0]), float(image_orientation[1]), float(image_orientation[2])])
phase_vector = numpy.array([float(image_orientation[3]), float(image_orientation[4]), float(image_orientation[5])])
mosaic_vector = numpy.cross(read_vector, phase_vector)
# normalize the vectors
read_vector /= numpy.linalg.norm(read_vector)
phase_vector /= numpy.linalg.norm(phase_vector)
mosaic_vector /= numpy.linalg.norm(mosaic_vector)
# create an empty array for the new bvecs
bvecs = numpy.zeros([len(sorted_dicoms), 3])
# for each slice calculate the new bvec
for index in range(0, len(sorted_dicoms)):
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[index][0]
else:
dicom_headers = sorted_dicoms[index]
# get the bval als this is needed in some checks
bval = common.get_is_value(dicom_headers[Tag(0x0019, 0x100c)])
# get the bvec if it exists in the headers
bvec = numpy.array([0, 0, 0])
if Tag(0x0019, 0x100e) in dicom_headers:
# in case of implicit VR the private field cannot be split into an array, we do this here
bvec = numpy.array(common.get_fd_array_value(dicom_headers[Tag(0x0019, 0x100e)], 3))
# if bval is 0 or the vector is 0 no projection is needed and the vector is 0,0,0
new_bvec = numpy.array([0, 0, 0])
if bval > 0 and not (bvec == [0, 0, 0]).all():
# project the bvec and invert the y direction
new_bvec = numpy.array(
[numpy.dot(bvec, read_vector), -numpy.dot(bvec, phase_vector), numpy.dot(bvec, mosaic_vector)])
# normalize the bvec
new_bvec /= numpy.linalg.norm(new_bvec)
bvecs[index, :] = new_bvec
# save the found bvecs to the file
common.write_bvec_file(bvecs, bvec_file)
return numpy.array(bvecs)
def _create_bvecs(sorted_dicoms, bvec_file):
"""
Calculate the bvecs and write the to a bvec file
# inspired by dicom2nii from mricron
# see http://users.fmrib.ox.ac.uk/~robson/internal/Dicom2Nifti111.m
"""
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[0][0]
else:
dicom_headers = sorted_dicoms[0]
# get the patient orientation
image_orientation = dicom_headers.ImageOrientationPatient
read_vector = numpy.array([float(image_orientation[0]), float(image_orientation[1]), float(image_orientation[2])])
phase_vector = numpy.array([float(image_orientation[3]), float(image_orientation[4]), float(image_orientation[5])])
mosaic_vector = numpy.cross(read_vector, phase_vector)
# normalize the vectors
read_vector /= numpy.linalg.norm(read_vector)
phase_vector /= numpy.linalg.norm(phase_vector)
mosaic_vector /= numpy.linalg.norm(mosaic_vector)
# create an empty array for the new bvecs
bvecs = numpy.zeros([len(sorted_dicoms), 3])
# for each slice calculate the new bvec
for index in range(0, len(sorted_dicoms)):
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[index][0]
else:
dicom_headers = sorted_dicoms[index]
# get the bval als this is needed in some checks
bval = common.get_is_value(dicom_headers[Tag(0x0019, 0x100c)])
# get the bvec if it exists in the headers
bvec = numpy.array([0, 0, 0])
if Tag(0x0019, 0x100e) in dicom_headers:
# in case of implicit VR the private field cannot be split into an array, we do this here
bvec = numpy.array(common.get_fd_array_value(dicom_headers[Tag(0x0019, 0x100e)], 3))
# if bval is 0 or the vector is 0 no projection is needed and the vector is 0,0,0
new_bvec = numpy.array([0, 0, 0])
if bval > 0 and not (bvec == [0, 0, 0]).all():
# project the bvec and invert the y direction
new_bvec = numpy.array(
[numpy.dot(bvec, read_vector), -numpy.dot(bvec, phase_vector), numpy.dot(bvec, mosaic_vector)])
# normalize the bvec
new_bvec /= numpy.linalg.norm(new_bvec)
bvecs[index, :] = new_bvec
# save the found bvecs to the file
common.write_bvec_file(bvecs, bvec_file)
def _create_bvals(sorted_dicoms, bval_file):
"""
Write the bvals from the sorted dicom files to a bval file
"""
bvals = []
for index in range(0, len(sorted_dicoms)):
if type(sorted_dicoms[0]) is list:
dicom_headers = sorted_dicoms[index][0]
else:
dicom_headers = sorted_dicoms[index]
bvals.append(common.get_is_value(dicom_headers[Tag(0x0019, 0x100c)]))
# save the found bvecs to the file
common.write_bval_file(bvals, bval_file)
return numpy.array(bvals)
